Text generation is an essential research area in artificial intelligence(AI)technology and natural language processing and provides key technical support for the rapid development of AI-generated content(AIGC).It is b...Text generation is an essential research area in artificial intelligence(AI)technology and natural language processing and provides key technical support for the rapid development of AI-generated content(AIGC).It is based on technologies such as natural language processing,machine learning,and deep learning,which enable learning language rules through training models to automatically generate text that meets grammatical and semantic requirements.In this paper,we sort and systematically summarize the main research progress in text generation and review recent text generation papers,focusing on presenting a detailed understanding of the technical models.In addition,several typical text generation application systems are presented.Finally,we address some challenges and future directions in AI text generation.We conclude that improving the quality,quantity,interactivity,and adaptability of generated text can help fundamentally advance AI text generation development.展开更多
基金Project supported by the National Natural Science Foundation of China(No.62272100)the Consulting Project of Chinese Academy of Engineering(No.2023-XY-09)+1 种基金the Major Project of the National Social Science Fund of China(No.21ZD11)the Fundamental Research Funds for the Central Universities,China。
文摘Text generation is an essential research area in artificial intelligence(AI)technology and natural language processing and provides key technical support for the rapid development of AI-generated content(AIGC).It is based on technologies such as natural language processing,machine learning,and deep learning,which enable learning language rules through training models to automatically generate text that meets grammatical and semantic requirements.In this paper,we sort and systematically summarize the main research progress in text generation and review recent text generation papers,focusing on presenting a detailed understanding of the technical models.In addition,several typical text generation application systems are presented.Finally,we address some challenges and future directions in AI text generation.We conclude that improving the quality,quantity,interactivity,and adaptability of generated text can help fundamentally advance AI text generation development.
